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the_mighty_skeetadon t1_iszprhg wrote

That can't be the only method, because if your model for generating fake papers differs significantly from somebody else's model, you will be both unable to detect those fake papers and unable to detect that you're failing.

Better is to have fake papers rejected from journals labeled thusly and to synthetically generate more fake papers with a wide variety of known approaches.

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stevewithaweave t1_iszusz3 wrote

I think the original commenter was referring to an architecture similar to GANs. I agree that including examples of fake papers would improve the model but is not required

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